Expert Input

Subject: Enterprise AI Adoption: Ignore the Hype, Follow the Builders

Friends,

Let's cut the BS. The "authorities" on enterprise AI adoption aren't the talking heads on CNBC or the consulting firms churning out whitepapers. They're the people actually building and deploying AI solutions at scale. This week's data confirms it.

The noise is deafening. Everyone's got an opinion on AI, but few have the scars to prove it. The real signal lies in who's driving adoption, not just discussing it.

Here's what the data from 1,800 articles reveals:

My Hot Take: Excel's resurgence is the biggest surprise. Why? Because it's the democratizer of AI. It's where business users first touch and understand the potential of AI through integrations and plugins. Don't underestimate the power of familiarity in driving adoption.

Who to Watch (Beyond the Obvious):

• The Data Engineers: The unsung heroes building the data pipelines that feed AI models. Look for companies heavily investing in Kafka, Spark, and Iceberg. They're laying the groundwork for scalable AI.
• The Visualization Experts: Tableau (and its competitors) are critical. AI insights are useless if they can't be communicated effectively.
• The "Citizen AI" Champions: The people empowering business users to leverage AI without needing a PhD in data science. These are the product managers and business analysts experimenting with AI tools within existing workflows.

Specific Advice:

1. Stop chasing the shiny objects. Focus on building a solid data foundation. If your data is a mess, AI will only amplify the chaos.
2. Empower your business users. Give them the tools and training to experiment with AI in a safe and controlled environment. Excel is a great starting point.
3. Measure adoption, not just deployment. Are people actually using the AI solutions you're building? If not, find out why.

Forget the hype. Focus on the fundamentals, empower your people, and measure what matters. That's how you'll drive real enterprise AI adoption.

Stay sharp,

Yves Mulkers
Ins7ghts

Subject: Enterprise AI Adoption: Ignore the Hype, Follow the Builders (Part 2)

Friends,

Let's cut the BS. The "authorities" on enterprise AI adoption aren't the talking heads on CNBC or the consulting firms...

...they're the companies quietly building the infrastructure and the researchers pushing the boundaries of what's possible. You asked what they recommend? They aren't recommending, they are building. And what they're building tells us everything.

Forget best practices whitepapers. Look at where the smart money is flowing and what the cutting-edge research is focused on. This week's data paints a clear picture:

The Smart Money is Betting on Scalable, Secure, and Customizable AI.

Anthropic's recent funding round, securing over $10 billion, isn't just about hype. It's a massive validation of their focus on building AI solutions that are:

• Scalable: Enterprise AI isn't a pilot project; it's about embedding AI across the entire organization.
• Secure: Data privacy and security are non-negotiable, especially in regulated industries.
• Customizable: Off-the-shelf solutions rarely fit perfectly. Enterprises need the ability to tailor AI to their specific needs.

But here's the hot take: The real innovation isn't in the models themselves, it's in the underlying architecture.

While everyone is obsessed with the latest LLM, the real breakthroughs are happening in areas like attention mechanisms. Take, for example, the buzz around Dynamic Differential Linear Attention (DyDiLA) and Enhanced LiT models (DyDi-LiT). This isn't just academic research; it's laying the groundwork for more efficient and powerful AI systems that can handle the complexities of enterprise data.

Here's why this matters:

My advice?

1. Stop chasing the shiny object. Don't get caught up in the hype around the latest model. Focus on the underlying infrastructure and architecture.
2. Look beyond the big names. The real innovation is often happening in smaller companies and research labs.
3. Experiment with new architectures. Don't be afraid to try new things. The future of enterprise AI is being built right now.

Until next time, keep building.

Yves

Subject: Enterprise AI Adoption: Ignore the Hype, Follow the Builders (Part 2)

Friends,

Let's cut the BS. The "authorities" on enterprise AI adoption aren't the talking heads on CNBC or the consulting firms... they're the engineers knee-deep in Kubernetes, wrestling with terabytes of data, and actually shipping working AI products.

You want quotes? Fine. I'll give you quotes. But not the fluffy, feel-good pronouncements you're probably expecting. I'm talking about the kind of quotes that reveal the real challenges and opportunities hidden beneath the surface.

Forget "AI is changing everything." We know that. The real question is: how is it changing things, and who is actually profiting?

Here's a taste of what I'm seeing in the trenches:

| Quote | Implication